In terms of limitations and directions for future work, one important limitation is that we only consider one type of adversarial loss to enforce fairness.
While this adversarial loss is theoretically motivated and known to perform well, there are other recent variations in the literature (e.g., [1]})—as well as related non-adversarial regularizers (e.g., [2]}). Also, while we considered imposing fairness over sets of attributes, we did not explicitly model subgroup-level fairness [3]}.
Extending and testing our framework with these alternatives is a natural direction for future work.
